AI Foundations

Data is the fuel, the model is the engine.

Most enterprise AI projects fail not because the models aren't good enough — but because the data isn't. CARRV produces the multimodal, structured capture format your AI initiatives actually need.

See the data primitive → Begin a pilot

Multimodal capture Training-data native Self-hosted Model-agnostic

The Data Problem 02

Enterprise data requires transformation for AI readiness.

Documentation serves humans, not models; this gap halts AI at the pilot stage.

The Reading Layer

Documents teach AI about the work.
Captures teach it to do it.

Documents serve AI well — for retrieval, Q&A, and grounding via RAG. But agentic AI — the kind that actually executes work — learns from structured trajectories: action, screen state, exceptions, outcomes. Captures supply what RAG can't: the signal that makes AI execute, not just describe.

Documents tell AI what should happen. Captures show what actually does.

Useretrieval / Q&A

Moderead

RAGyes

Agentsno

CARRV Capture Event

cap_a91f3c7e2b40

01 Actor & Time

timestamp2026-04-28T14:23:34.881Z

actorpaul.dimitri@finco.com

roleAP_Specialist · okta

02 Action

typeclick

target[Approve & Send]

appsap.ariba/vendor/30421

latency12 ms

03 Context

workflowvendor.banking_change

screensha256:7e2b40…

04 Multimodal

pixels1920×1080 · png

doma11y_tree.json

state3 fields · masked

✓ verification_success · banking change validated via Plaid

⬢ signed · Ed25519

⬢━⬢━⬢━⬢

sha256:a91f3c…7e2b40

Use Cases 03

Same data. Every AI workflow.

Captured once, the same data feeds every layer of the AI stack — discovery, training, fine-tuning, monitoring, governance. Here's how serious AI teams put it to work.

01 / Discovery

Process Discovery & Automation Candidates

CARRV passively captures how work actually happens — sequences, exceptions, handoffs, edge cases — so automation teams stop guessing which processes are real candidates.

High-volume · friction-mapped

01 / 10

Governance 05

The same primitive satisfies regulators.

Modern AI governance frameworks all require the same thing: structured, attributable, verifiable records of how AI systems behaved in production. CARRV produces them by default — your team turns them into the answers regulators ask for.

Audit · attribution

Audit Trails

Every captured action carries actor, time, screen state, and signature — at the source.

CARRV produces

signed events actor attribution ed25519 signatures

Teams leverage

→Audit reports on demand

→Forensic reconstruction

→Independent chain-of-custody

Risk · monitoring

Risk Measurement

Continuous behavior records — the substrate for measuring how AI behaves in production.

CARRV produces

capture stream structured records queryable indexes

Teams leverage

→Drift & override metrics

→Production anomaly flags

→Risk dashboards on the stream

Provenance · lineage

Versioning & Provenance

Every capture is hashed, signed, and linkable to the model version it informed.

CARRV produces

sha256 hashes corpus manifests capture IDs

Teams leverage

→Training-data lineage

→Output reproducibility

→End-to-end tamper-evidence

Architecture06

Plugs into the AI stack you already have.

CARRV is the upstream capture layer. Records flow into your existing ML infrastructure — no rip-and-replace, no proprietary lock-in.

JSON Standards· Zero Lock-in· SOC2-Ready· Offline-First

Versus the Status Quo 08

Same human at the desk. Three different things reach the model.

What the AI gets to learn from depends entirely on how you captured the work.

01 / DEFAULT

Documentation

SOPs · Confluence · Word

Human at desk

Manual write-up

Markdown / DOCX

AI Receives Aspirational text "What should happen" — model learns intent, not behavior.

02 / WORKAROUND

Screen Recordings

Loom · Camtasia · OBS

Human at desk

Video recording

.MP4 file

AI Receives Pixel stream No actions, no DOM, no structure. Heavy preprocessing required.

03 / CARRV

CARRV

Multi-signal capture · structured

Human at desk

Action + Pixel + DOM + UIA + OCR

.crv archive

AI Receives Training corpus Native multimodal records — fine-tuning ready.

Start a Pilot

Capture one workflow.
Compare your AI roadmap.

Three months. One cohort. The receipts are yours, the format is open, and the records are independently verifiable. If the data isn't meaningfully better than what your competitors have, you'll know inside a quarter.

Begin a Pilot →

Self-hosted· Open schema· 30-minute call

Data is the fuel, the model is the engine.

Enterprise data requires transformation for AI readiness.

Documents teach AI about the work.
Captures teach it to do it.

Same data. Every AI workflow.

Process Discovery & Automation Candidates

The same primitive satisfies regulators.

Audit Trails

Risk Measurement

Versioning & Provenance

Plugs into the AI stack you already have.

Same human at the desk. Three different things reach the model.

Capture one workflow.
Compare your AI roadmap.

Request a Demo

You're all set

Start your
pilot.

Pilot request received

Data is the fuel, the model is the engine.

Enterprise data requires transformation for AI readiness.

Documents teach AI about the work.Captures teach it to do it.

Same data. Every AI workflow.

Process Discovery & Automation Candidates

The same primitive satisfies regulators.

Audit Trails

Risk Measurement

Versioning & Provenance

Plugs into the AI stack you already have.

Same human at the desk. Three different things reach the model.

Capture one workflow. Compare your AI roadmap.

Request a Demo

You're all set

Start yourpilot.

Pilot request received

Documents teach AI about the work.
Captures teach it to do it.

Capture one workflow.
Compare your AI roadmap.

Start your
pilot.